openpilot/tinygrad_repo/examples/mlperf
Vehicle Researcher c5d5c5d1f3 openpilot v0.10.1 release
date: 2025-10-24T00:30:59
master commit: 405631baf9685e171a0dd19547cb763f1b163d18
2025-10-24 00:31:03 -07:00
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scripts openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
training_submission_v4.0/tinycorp openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
training_submission_v4.1/tinycorp openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
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training_submission_v5.1/tinycorp openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
dataloader.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
helpers.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
initializers.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
losses.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
lr_schedulers.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
metrics.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
model_eval.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
model_spec.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
model_train.py openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00
README openpilot v0.10.1 release 2025-10-24 00:31:03 -07:00

Each model should be a clean single file.
They are imported from the top level `models` directory

It should be capable of loading weights from the reference imp.

We will focus on these 5 models:

# Resnet50-v1.5 (classic) -- 8.2 GOPS/input
# Retinanet
# 3D UNET (upconvs)
# RNNT
# BERT-large (transformer)

They are used in both the training and inference benchmark:
https://mlcommons.org/en/training-normal-21/
https://mlcommons.org/en/inference-edge-30/
And we will submit to both.

NOTE: we are Edge since we don't have ECC RAM